Code accompanying the paper "Diverse projection ensembles for distributional reinforcement learning"
DOI:10.4121/6b996f9c-27a9-4332-a0b6-d186ac6c4467.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future.
For a link that will always point to the latest version, please use
DOI: 10.4121/6b996f9c-27a9-4332-a0b6-d186ac6c4467
DOI: 10.4121/6b996f9c-27a9-4332-a0b6-d186ac6c4467
Datacite citation style
Zanger, Moritz A.; Boehmer, Wendelin; Spaan, M.T.J. (Matthijs) (2025): Code accompanying the paper "Diverse projection ensembles for distributional reinforcement learning". Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/6b996f9c-27a9-4332-a0b6-d186ac6c4467.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Software
This is the official code repository of projection-ensemble DQN, accompanying the paper "Diverse projection ensembles for distributional reinforcement learning" (ICLR 2024).
History
- 2025-08-15 first online, published, posted
Publisher
4TU.ResearchDataFormat
.pyAssociated peer-reviewed publication
Diverse Projection Ensembles for Distributional Reinforcement LearningReferences
Code hosting project url
https://github.com/anyboby/diverse-projection-ensemblesFunding
- Epistemic AI (grant code 964505) [more info...] EXCELLENT SCIENCE - Future and Emerging Technologies (FET) (EU Horizons 2020)
Organizations
Delft University of Technology, Faculty of Electrical Engineering, Mathematics and Computer Science, Department of Intelligent Systems, Sequential Decision Making GroupTo access the source code, use the following command:
git clone https://data.4tu.nl/v3/datasets/26e6f861-05e8-4446-b58b-4c045bf8b60c.git "diverse-projection-ensembles"